Systems and methods for environmental analysis based upon vehicle sensor data

ABSTRACT

A system for analyzing the environment of a vehicle i) receives a plurality of data from at least one sensor associated with a vehicle, such that the plurality of data includes at least one environmental condition at a location; (ii) analyzes the plurality of data to determine the at least one environmental condition at the location; (iii) determines a condition of a building at the location based upon the at least one environmental condition; (iv) determines an insurance product for the building based upon the determined condition associated with the building; and (v) generates an insurance quote for the insurance product. As a result, the speed and accuracy of insurance providers learning about potential clients and the conditions of the potential client&#39;s property and needs is increased.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of U.S. patentapplication Ser. No. 16/834,679, filed Mar. 30, 2020, entitled “SYSTEMSAND METHODS FOR ENVIRONMENTAL ANALYSIS BASED UPON VEHICLE SENSOR DATA,”which is a continuation of U.S. patent application Ser. No. 15/486,067,filed Apr. 12, 2017, entitled “SYSTEMS AND METHODS FOR ENVIRONMENTALANALYSIS BASED UPON VEHICLE SENSOR DATA,” which issued as U.S. Pat. No.10,643,285 on May 5, 2020, which claims the benefit of priority to U.S.Provisional Patent Application Ser. No. 62/353,762, filed Jun. 23, 2016,entitled “SYSTEMS AND METHODS FOR ENVIRONMENTAL ANALYSIS BASED UPONVEHICLE SENSOR DATA,” and to U.S. Provisional Patent Application Ser.No. 62/363,945, filed Jul. 19, 2016, entitled “SYSTEMS AND METHODS FORENVIRONMENTAL ANALYSIS BASED UPON VEHICLE SENSOR DATA,” the entirecontents of which are hereby incorporated by reference in theirentirety.

FIELD OF THE INVENTION

The present disclosure relates to using vehicle sensor data forenvironmental analysis, and a network-based system and method foranalyzing the environment of a vehicle, and determining businessopportunities based upon the analysis.

BACKGROUND

In many cases, advertising is low value because there is no indicationthat the product or service is needed. Frequent ads on the Internet,cold calls, and door-to-door sales serve as the initial contact withhopes of a future sale, but the likelihood of completing a sale is lowbased upon the blind initial contact. Ads on the Internet may betriggered when an individual searches, clicks, or otherwise indicates aneed.

However, there are cases, where the individual may not even know that hehas a need. For instance, if a tree in an individual's front yard hasinsect damage, but the individual may not notice or recognize thesignificance. In this instance, the individual may not be aware that hisproperty is in need of maintenance and/or who would perform thatmaintenance. Additionally, no Internet ads are triggered to address thatneed.

BRIEF SUMMARY

The present embodiments may relate to systems and methods for analyzingthe environment of a vehicle. An environment monitoring system, asdescribed herein, may include an environment monitoring (“EM”) computerdevice that is in communication with a mobile computer device associatedwith a user. The EM computer device may be configured to (i) receive aplurality of data from at least one sensor associated with a vehicle,where the plurality of data includes at least one environmentalcondition that is proximate to the vehicle during at least one point intime and includes at least one of: a condition of a building, acondition of vegetation, a condition of a public thoroughfare, a weathercondition, and a vehicular accident that the vehicle was not involvedin. The plurality of data may include a plurality of location data and aplurality of sensor readings. Each sensor reading may be associated witha location of the plurality of locations. The EM computer device may befurther configured to (ii) determine a location associated with the atleast one environmental condition based upon the plurality of data;(iii) determine a user account associated with the determined location;(iv) determine the at least one environmental condition by comparingdata associated with a plurality of separate points in time, where theenvironmental condition is proximate to the vehicle at the plurality ofseparate points in time; (v) store a plurality of historical sensordata; (vi) compare the plurality of data to the historical data todetermine the at least one environmental condition; (vii) analyze theplurality of data to determine the at least one environmental condition;(viii) determine at least one actionable item based upon the at leastone environmental condition; (ix) determine at least one provider basedupon the actionable item; and/or (x) transmit a message to the at leastone provider, such that the message includes the at least one actionableitem and where the provider is configured to (a) transmit a message tothe user account or (b) transmit an advertisement associated with the atleast one actionable item. The EM computing device may includeadditional, less, or alternate functionality, including that discussedelsewhere herein.

At least one advantage of this system is that it provides more accurateleads to businesses based upon the actual needs of potential customers.This reduces the need for blind sales calls. Furthermore, the use ofsensor data allows for providing additional information about changes toan environment overtime including potential actionable items, withoutrequiring constant manual inspection. Another advantage of the system isto provide additional information about vehicular crashes to improvemodeling of the scenario of the vehicular crash. Another advantage ofthe system is reducing potential injuries in a vehicular accident byinducing passengers to reposition and/or change direction of facing. Afurther advantage is reducing damage to at least one of a vehicle and/orpassengers by repositioning the vehicle prior to impact.

In one aspect, a computer system for analyzing the environment of avehicle, and/or improving the functioning of a computer, may beprovided. The computer system may include at least one processor (and/orassociated transceiver) in communication with at least one memorydevice. The at least one processor (and/or associated transceiver) maybe configured or programmed to: (1) receive a plurality of data from atleast one sensor associated with a vehicle, wherein the plurality ofdata includes at least one environmental condition; (2) analyze theplurality of data to determine the at least one environmental condition;(3) determine at least one actionable item based upon the at least oneenvironmental condition; (4) determine at least one provider based uponthe actionable item; and/or (5) transmit a message to the at least oneprovider or to a provide computing, such as via wireless communicationor data transmission over one or more radio links or wirelesscommunication channels, wherein the message includes the at least oneactionable item to facilitate communication to providers about potentialactionable items. The computer system may have additional, less, oralternate functionality, including that discussed elsewhere herein.

In another aspect, a computer-based method for analyzing the environmentof a vehicle, and/or improving the functioning of a computer, may beprovided. The method may be implemented on an environment monitoring(“EM”) server that includes at least one processor (and/or associatedtransceiver) in communication with at least one memory device. Themethod may include: (1) receiving, at the EM server (such as viawireless communication or data transmission over one or more radio linksor wireless communication channels), a plurality of data from at leastone sensor (and/or transceivers) associated with a vehicle, wherein theplurality of data includes at least one environmental condition; (2)analyzing, by the EM server, the plurality of data to determine the atleast one environmental condition; (3) determining, by the EM server, atleast one actionable item based upon the at least one environmentalcondition; (4) determining, by the EM server, at least one providerbased upon the actionable item; and/or (5) transmitting a message to theat least one provider or provider computing device (such as via wirelesscommunication or data transmission over one or more radio links orwireless communication channels), wherein the message includes the atleast one actionable item to facilitate communication to providers aboutpotential actionable items. The computer system may have additional,less, or alternate functionality, including that discussed elsewhereherein.

In yet another aspect, at least one non-transitory computer-readablestorage media having computer-executable instructions embodied thereonmay be provided. When executed by at least one processor, thecomputer-executable instructions cause the processor (and/or anassociated transceiver) to: (1) receive a plurality of data from atleast one sensor associated with a vehicle, wherein the plurality ofdata includes at least one environmental condition; (2) analyze theplurality of data to determine the at least one environmental condition;(3) determine at least one actionable item based upon the at least oneenvironmental condition; (4) determine at least one provider based uponthe actionable item; and/or (5) transmit a message to the at least oneprovider, wherein the message includes the at least one actionable itemto facilitate communication to providers about potential actionableitems. The computer system may have additional, less, or alternatefunctionality, including that discussed elsewhere herein.

In still another aspect, a computer system for detecting a vehicularcrash may be provided. The computer system may include at least oneprocessor, sensor, and/or transceiver in communication with at least onememory device, the at least one processor, sensor, and/or transceiver.The at least one processor may be programmed to (1) (locally orremotely) receive data from the at least one sensor (such as via wiredor wireless communication); (2) determine that a potential vehicularcrash is imminent based upon the received data; and/or (3) perform atleast one action to reduce a severity of the potential vehicular crashprior to impact. The computer system may include additional, less, oralternate functionality, including that discussed elsewhere herein.

In a different aspect, a computer-based method for detecting a vehicularcrash may be provided. The method may include (1) receiving data from atleast one sensor of a vehicle; (2) determining, at the EM server, that apotential vehicular crash is imminent based upon the received data;and/or (3) performing at least one action to reduce a severity of thepotential vehicular crash prior to impact. The method may includeadditional, less, or alternate actions, including those discussedelsewhere herein.

In still another aspect, at least one non-transitory computer-readablestorage media having computer-executable instructions embodied thereonmay be provided. When executed by at least one processor, thecomputer-executable instructions cause the processor (and/or anassociated transceiver) to: (1) receive data from at least one sensor ofa vehicle; (2) determine that a potential vehicular crash is imminentbased upon the received data; and/or (3) perform at least one action toreduce a severity of the potential vehicular crash prior to impact. Thestorage media may include additional, less, or alternate actions,including those discussed elsewhere herein.

In yet another aspect, a computer system for analyzing the environmentof a vehicle may be provided. The computer system may include at leastone processor in communication with at least one memory device. The atleast one processor is programmed to receive a plurality of data from atleast one sensor associated with a vehicle. The plurality of dataincludes at least one environmental condition. The at least oneprocessor is also programmed to analyze the plurality of data todetermine the at least one environmental condition, determine at leastone actionable item based upon the at least one environmental condition,determine an insurance policy associated with the at least oneactionable item, generate a virtual insurance claim based upon the atleast one actionable item, and/or transmit the virtual insurance claimto an insurance provider associated with the insurance policy tofacilitate proactive action on filing insurance claims. The computersystem may include additional, less, or alternate actions, includingthose discussed elsewhere herein.

In still another aspect, a computer-based method for analyzing theenvironment of a vehicle may be provided. The method may be implementedon an environment monitoring (“EM”) server including at least oneprocessor in communication with at least one memory device. The methodmay include receiving, at the EM server, a plurality of data from atleast one sensor associated with a vehicle. The plurality of dataincludes at least one environmental condition. The method may alsoinclude analyzing, by the EM server, the plurality of data to determinethe at least one environmental condition, determining, by the EM server,at least one actionable item based upon the at least one environmentalcondition, determining, by the EM server, an insurance policy associatedwith the at least one actionable item, generating a virtual insuranceclaim based upon the at least one actionable item, and/or transmittingthe virtual insurance claim to an insurance provider associated with theinsurance policy to facilitate proactive action on filing insuranceclaims. The method may include additional, less, or alternate actions,including those discussed elsewhere herein.

In still another aspect, at least one non-transitory computer-readablestorage media having computer-executable instructions embodied thereonmay be provided. When executed by at least one processor, thecomputer-executable instructions cause the processor (and/or anassociated transceiver) to receive a plurality of data from at least onesensor associated with a vehicle. The plurality of data includes atleast one environmental condition. The computer-executable instructionsmay cause the processor (and/or an associated transceiver) to analyzethe plurality of data to determine the at least one environmentalcondition, determine at least one actionable item based upon the atleast one environmental condition, determine an insurance policyassociated with the at least one actionable item, generate a virtualinsurance claim based upon the at least one actionable item, and/ortransmit the virtual insurance claim to an insurance provider associatedwith the insurance policy to facilitate proactive action on filinginsurance claims. The storage media may include additional, less, oralternate actions, including those discussed elsewhere herein.

In yet another aspect, a computer system for analyzing the environmentof a vehicle may be provided. The computer system may include at leastone processor in communication with at least one memory device. The atleast one processor is programmed to receive a plurality of data from atleast one sensor associated with a vehicle. The plurality of dataincludes at least one environmental condition at a location. The atleast one processor may also be programmed to analyze the plurality ofdata to determine the at least one environmental condition at thelocation, determine a condition of a building at the location based uponthe at least one environmental condition, determine an insurance productfor the building based upon the determined condition associated with thebuilding, and/or generate an insurance quote for the insurance product.The computer system may include additional, less, or alternate actions,including those discussed elsewhere herein.

In still another aspect, a computer-based method for analyzing theenvironment of a vehicle may be provided. The method may be implementedon an environment monitoring (“EM”) server including at least oneprocessor in communication with at least one memory device. The methodincludes receiving, at the EM server, a plurality of data from at leastone sensor associated with a vehicle. The plurality of data includes atleast one environmental condition at a location. The method may alsoinclude analyzing, by the EM server, the plurality of data to determinethe at least one environmental condition at the location, determining,by the EM server, a condition of a building at the location based uponthe at least one environmental condition, determining, by the EM server,an insurance product for the building based upon the determinedcondition associated with the building, and/or generating an insurancequote for the insurance product. The method may include additional,less, or alternate actions, including those discussed elsewhere herein.

In still another aspect, at least one non-transitory computer-readablestorage media having computer-executable instructions embodied thereonmay be provided. When executed by at least one processor, thecomputer-executable instructions cause the processor (and/or anassociated transceiver) to receive a plurality of data from at least onesensor associated with a vehicle. The plurality of data includes atleast one environmental condition at a location. The computer-executableinstructions may also cause the processor (and/or an associatedtransceiver) to analyze the plurality of data to determine the at leastone environmental condition at the location, determine a condition of abuilding at the location based upon the at least one environmentalcondition, determine an insurance product for the building based uponthe determined condition associated with the building, and/or generatean insurance quote for the insurance product. The storage media mayinclude additional, less, or alternate actions, including thosediscussed elsewhere herein.

Advantages will become more apparent to those skilled in the art fromthe following description of the preferred embodiments which have beenshown and described by way of illustration. As will be realized, thepresent embodiments may be capable of other and different embodiments,and their details are capable of modification in various respects.Accordingly, the drawings and description are to be regarded asillustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The Figures described below depict various aspects of the systems andmethods disclosed therein. It should be understood that each Figuredepicts an embodiment of a particular aspect of the disclosed systemsand methods, and that each of the Figures is intended to accord with apossible embodiment thereof. Further, wherever possible, the followingdescription refers to the reference numerals included in the followingFigures, in which features depicted in multiple Figures are designatedwith consistent reference numerals.

There are shown in the drawings arrangements which are presentlydiscussed, it being understood, however, that the present embodimentsare not limited to the precise arrangements and are instrumentalitiesshown, wherein:

FIG. 1 illustrates a schematic diagram of an exemplary vehicle.

FIG. 2 illustrates a flow chart of an exemplary process of analyzing theenvironment of a vehicle, such as of the vehicle shown in FIG. 1.

FIG. 3 illustrates a flow chart of an exemplary computer-implementedprocess for analyzing the environment of a vehicle shown in FIG. 2.

FIG. 4 illustrates a simplified block diagram of an exemplary computersystem for implementing the process shown in FIG. 1.

FIG. 5 illustrates an exemplary configuration of a client computerdevice shown in FIG. 4, in accordance with one embodiment of the presentdisclosure.

FIG. 6 illustrates an exemplary configuration of a server shown in FIG.4, in accordance with one embodiment of the present disclosure.

FIG. 7 illustrates a flow chart of an exemplary computer-implementedprocess of detecting a vehicular crash using the system shown in FIG. 4.

FIG. 8 illustrates a diagram of components of one or more exemplarycomputing devices that may be used in the system shown in FIG. 4.

FIG. 9 illustrates a flow chart of another exemplarycomputer-implemented process for analyzing the environment of a vehicleshown in FIG. 2.

FIG. 10 illustrates a flow chart of a further exemplarycomputer-implemented process for analyzing the environment of a vehicleshown in FIG. 2.

The Figures depict preferred embodiments for purposes of illustrationonly. One skilled in the art will readily recognize from the followingdiscussion that alternative embodiments of the systems and methodsillustrated herein may be employed without departing from the principlesof the invention described herein.

DETAILED DESCRIPTION OF THE DRAWINGS

The present embodiments may relate to, inter alia, systems and methodsfor analyzing the environment of a vehicle and determining at least onebusiness opportunities based upon the environment. In an exemplaryembodiment, the process is performed by an environment monitoring (“EM”)computer device, also known as an environment monitoring (“EM”) server.

In the exemplary embodiment, a vehicle includes a vehicle computerdevice and a plurality of sensors. A process begins with the vehiclecomputer device in-transit from one location. While in-transit, theplurality of sensors may continuously scan the environment around thevehicle. For example, the sensors may take images of buildings, plants,and other vehicles as a part of normal operation while the vehicle isin-transit. These images may be in the visible spectrum, infraredspectrum, high-contrast, and/or three-dimensional (3D) images. In theexemplary embodiment, the vehicle controller is in communication with adatabase and an environment monitoring (“EM”) computer device, alsoknown as an EM server. The EM server is also in communication with oneor more 3^(rd) Party providers, such as via wireless communication ordata transmission over one or more radio links or wireless communicationchannels. The vehicle computer device and EM server may include softwarethat allows them to function as is described herein.

The vehicle computer device may transmit the sensor data to thedatabase. In some embodiments, the vehicle computer device may transmitthe data continuously to the database. In other embodiments, the vehiclecomputer device may transmit the data when the vehicle is stopped, suchas at a stoplight.

In still other embodiments, the vehicle computer device may transmit thedata to the database when the vehicle is connected to a network througha wired connection, such as at a recharging station. Alternatively, thevehicle may be connected to a wireless communication network through awireless connection, such as at a wireless or other recharging station.Transmitting the data may occur at a convenient processing or datatransmission time(s) based upon prioritization methods such as datatransmission costs (e.g., cellular vs. free Wi-Fi) or computationalcosts (e.g., vehicle busy processing autonomous or accident avoidance sothat may delay processing until the vehicle is parked, or until vehicleprocessing load has decreased.

In the exemplary embodiment, the database stores all of the datareceived from the sensors. In some embodiments, the database may storethe raw data feeds. In other embodiments, the database may store asub-set of the data from the sensors. In some embodiments, the databasemay store sensor data from a plurality of vehicles. The database storesthe data that allows the EM server to function as is described herein.

In the exemplary embodiment, the EM server feeds the received sensordata through a comparative algorithm that contains historical data. Insome embodiments, the EM server compares the received sensor data tohistorical sensor data from the same vehicle. In other embodiments, theEM server compares the sensor data to historical sensor data from othervehicles.

In the exemplary embodiment, the EM server determines if there is anactionable change in the environment of the vehicle. In a first example,sensor data may contain images of a house that the vehicle drives past.In the exemplary embodiment, sensor data may include location data, suchas from a GPS unit. Based upon the location of the vehicle at the timethat sensor data was taken, the EM server may determine the address ofthe house. The EM server may compare the received images of the house tohistorical images of the house. Based upon the comparison, the EM servermay determine that there is damage to the house that has occurred sincethe last time the house was sensed. The EM server may compare the sensordata of the house to sensor data of other houses and determine apotentially hazardous or dangerous condition of the house based upon thecomparison. In these examples, the EM server determines that there is anactionable change, such as repairs that need to be made to the house, orpreventive or mitigating actions that should be taken.

In a second example, sensor data may contain images of a plant, such asa tree. The EM server may compare the sensor data of the tree to sensordata from other trees of the same type and determine that the tree has adisease or requires trimming to reduce various risks (such as theft orwildfire). In this example, the EM server determines that there is anactionable change, such as actions that need to be taken to improve thehealth of the tree. In a third example, sensor data may contain imagesof a public thoroughfare, such as a road or sidewalk. The EM server maydetermine that the public thoroughfare requires repair. In someembodiments, the EM server may determine a priority or severity of anyneeded repair or actionable item.

In the exemplary embodiment, if the EM server determines that there areno actionable changes, the system continues scanning and analyzing theenvironment of vehicle. If the EM server determines that there is anactionable change, the EM server logs the change in the database. The EMserver determines a 3^(rd) Party to notify about the actionable changeand transmits the actionable change to the 3^(rd) Party. The 3^(rd)Party may perform an action based upon the actionable item or changes.The EM server may refine one or more algorithms based upon the sensordata and the determined actionable item.

In the exemplary embodiment, the 3^(rd) Party may be a subscriber to aservice that monitors for potential actionable items. For example, the3^(rd) Party may be a landlord that owns a plurality of rentalbuildings. The EM server may determine that one of the landlord'sbuildings is in need of repairs, that one of the trees in his yard has adisease, that one of the walkways near his building has a dangerouscondition, and/or that one of his tenants is failing to perform propermaintenance, e.g., mow the lawn. The notification of the actionable itemmay inform the landlord of a previously unknown issue that requiresaction on his or her part. The 3^(rd) Party may also be a homeowner'sassociation and actionable items may include lawn maintenance, buildingchanges, and other issues potentially related to the homeowner'scharter.

In other examples, the 3^(rd) Party is a service provider, such as atree trimmer, a roofer, or other construction company. In theseexamples, the 3^(rd) Party may transmit one or more advertisements to aperson associated with the actionable item, such as the homeowner. Forexample, the EM server may determine that there is damage to the sidingof the house, determine one or more 3^(rd) Parties that may repair theissue, and/or notify those 3^(rd) Parties.

In still other examples, the 3^(rd) Party may be a municipal serviceprovider, such as a road repair crew or a building inspector. In theexample of road repair crew, the actionable item may be one or morepotholes or other potential hazards. In some embodiments, the hazard maybe a broken water pipe and/or flooding on the road. In the example of abuilding inspector, the EM server may determine that a new addition orout building was added to a property and notify the building inspectorthat there may be a permitting issue. In another example, the EM servermay compare the timing of traffic lights to determine if there is anissue, or if the timing of one or more lights may need to be adjusted.

In still further examples, the sensors may observe a vehicular accidentand the EM server may use sensor data to recreate the accident andprovide the accident information to the police or the appropriateinsurance companies. In this example, the vehicle may not be involved inthe vehicular accident.

In yet another example, the sensors may observe weather conditions. Forexample during a hail storm, the sensors may measure the size of hailthrough images and the rate of hail based upon the sound of the hailhitting the vehicle or the ground. The EM server may receive sensor dataabout the hail from multiple vehicles in multiple locations to determinewhere the hail fell and how serious it was in different areas. Then theEM server may determine one or more construction companies that would beinterested in this information for lead generation purposes.

At least one of the technical problems addressed by this system mayinclude: (i) discovering potential business opportunities; (ii)accurately monitoring conditions of one or more structures for users;(iii) improving the speed and accuracy of reconstructing a vehicularaccident scenario; (iv) determining that a vehicular accident isoccurring or may be occurring; and/or (v) reducing the severity of avehicular accident.

The technical effect achieved by this system may be at least one of: (i)automated discovery of potential business opportunities; (ii) automatedwarning of condition changes at one or more structures; (iii) automateddetection of vehicular accidents as they are occurring; and/or (iv)automatically reacting to a vehicular accident reduce the severity ofthe vehicular accident.

The methods and systems described herein may be implemented usingcomputer programming or engineering techniques including computersoftware, firmware, hardware, or any combination or subset thereof,wherein the technical effects may be achieved by performing at least oneof the following steps: (a) receiving, at an environment monitoring(“EM”) server, a plurality of data from at least one sensor associatedwith a vehicle, where the plurality of data includes at least oneenvironmental condition; (b) analyzing, by the EM server, the pluralityof data to determine the at least one environmental condition; (c)determining, by the EM server, at least one actionable item based uponthe at least one environmental condition; (d) determining, by the EMserver, at least one provider based upon the actionable item; and (e)transmitting a message to the at least one provider, wherein the messageincludes the at least one actionable item to facilitate communication toproviders about potential actionable items.

Additional technical effects may be achieved by performing at least oneof the following steps: (a) receiving data from a sensor; (b)determining that a potential vehicular crash is imminent based upon thereceived data; and/or (c) performing at least one action to reduce aseverity of the potential vehicular crash prior to impact to facilitatereducing injuries and/or damage caused by the vehicular crash.

Exemplary Vehicle

FIG. 1 depicts a view of an exemplary vehicle 100. In some embodiments,vehicle 100 may be an autonomous vehicle capable of fulfilling thetransportation capabilities of a traditional automobile or othervehicle. In these embodiments, vehicle 100 may be capable of sensing itsenvironment and navigating without human input. In other embodiments,vehicle 100 is a manual vehicle, such as a traditional automobile thatis directly controlled by a driver 115.

Vehicle 100 may include a plurality of sensors 105 and a vehiclecomputer device 110, also known as a vehicle controller 110. Theplurality of sensors 105 may detect the current surroundings andlocation of vehicle 100. Plurality of sensors 105 may include, but arenot limited to, radar, LIDAR, Global Positioning System (GPS), videodevices, imaging devices, cameras, audio recorders, and computer vision.Plurality of sensors 105 may also include sensors that detect conditionsof vehicle 100, such as velocity, acceleration, gear, braking, and otherconditions related to the operation of vehicle 100. In some embodiments,plurality of sensors 105 may detect the presence of driver 115 and oneor more passengers 120 in vehicle 100. In these embodiments, pluralityof sensors 105 may detect the presence of fastened seatbelts, the weightin each seat in vehicle 100, heat signatures, or any other method ofdetecting information about driver 115 and passengers 120 in vehicle100.

Vehicle computer device 110 may interpret the sensory information toidentify appropriate navigation paths, detect threats, and react toconditions. In some embodiments, vehicle computer device 110 may be ableto communicate with one or more remote computer devices, such as mobiledevice 125. In the example embodiment, mobile device 125 is associatedwith driver 115 and includes one or more internal sensors, such as anaccelerometer. Mobile device 125 may be capable of communicating withvehicle computer device 110 wirelessly. In addition, vehicle computerdevice 110 and mobile device 125 may be configured to communicate withcomputer devices located remotely from vehicle 100.

While vehicle 100 may be an automobile in the exemplary embodiment, inother embodiments, vehicle 100 may be, but is not limited to, othertypes of ground craft, aircraft, and watercraft vehicles.

Exemplary Process for Analyzing Vehicle Environment

FIG. 2 illustrates a flow chart of an exemplary process 200 of analyzingthe environment of a vehicle, such as of vehicle 100 shown in FIG. 1. Inthe exemplary embodiment, vehicle controller 110 may be in communicationwith a database 202 and an environment monitoring (“EM”) computer device204, also known as an EM server 204. EM server 204 may also be incommunication with one or more 3^(rd) Party providers 206. Vehiclecomputer device 110 and EM server 204 may include software that allowsthem to function as is described herein.

In the exemplary embodiment, vehicle 100 (shown in FIG. 1) includesvehicle computer device 110 and a plurality of sensors 105 (shown inFIG. 1). Process 200 begins with vehicle computer device 110 in-transit208 from one location. While in-transit 208, the plurality of sensors105 may continually scan 210 the environment around vehicle 100. Forexample, sensors 105 may take images of buildings, plants, and othervehicles as a part of normal operation while vehicle 100 is in-transit.These images may be in the visible spectrum, infrared spectrum,high-contrast, and/or three-dimensional (3D) images.

Vehicle computer device 110 may transmit 212 the sensor data to database202. In some embodiments, vehicle computer device 110 may transmit 212the data continuously to database 202. In other embodiments, vehiclecomputer device 110 may transmit 212 the data when vehicle 100 isstopped, such as at a stoplight. In still other embodiments, vehiclecomputer device 110 may transmit 212 the data to database 202 whenvehicle 100 is connected to a network through a wired connection, suchas at a recharging station.

In the exemplary embodiment, database 202 stores 214 all of the datareceived from sensors 105. In some embodiments, database 202 may store214 the raw data feeds. In other embodiments, database 202 may store 214a sub-set of the data from sensors 105. In some embodiments, database202 may store sensor data from a plurality of vehicles 100. Database 202stores the data that allows EM server 204 to function as is describedherein.

In the exemplary embodiment, EM server 204 feeds 216 the received sensordata through a comparative algorithm containing historical data. In someembodiments, EM server 204 compares the received sensor data tohistorical sensor data from the same vehicle 100. In other embodiments,EM server 204 compares the sensor data to historical sensor data fromother vehicles.

In the exemplary embodiment, EM server 204 determines 218 if there is anactionable change in the environment of vehicle 100. In a first example,sensor data may contain images of a house that vehicle 100 drives past.In the exemplary embodiment, sensor data may include location data, suchas from a GPS. Based upon the location of vehicle 100 at the time thatsensor data was taken, EM server 204 may determine the address of thehouse. EM server 204 may compare the received images of the house tohistorical images of the house. Based upon the comparison, EM server 204may determine that there is damage to the house that has occurred sincethe last time the house was sensed. EM server 204 may compare the sensordata of the house to sensor data of other houses and determine apotentially hazardous or dangerous condition of the house based upon thecomparison. In these examples, EM server 204 determines that there is anactionable change, for example repairs that need to be made to thehouse.

In a second example, sensor data may contain images of a plant, such asa tree. EM server 204 may compare the sensor data of the tree to sensordata from other trees of the same type and determine that the tree has adisease or requires trimming. In this example, EM server 204 determinesthat there is an actionable change, such as actions that need to betaken to improve the health of the tree.

In a third example, sensor data may contain images of a publicthoroughfare, such as a road or sidewalk. EM server 204 may determinethat the public thoroughfare requires repair. In some embodiments, EMserver 204 may determine a priority or severity of any needed repairs oractionable items.

In the exemplary embodiment, if EM server 204 determines 218 that thereare no actionable changes, system 200 continues scanning and analyzingthe environment of vehicle 100. If EM server 204 determines 218 thatthere is an actionable change, EM server 204 logs 220 the change indatabase 202. EM server 204 determines 222 a 3^(rd) Party 206 to notifyabout the actionable change and transmits the actionable change to the3^(rd) Party 206. 3^(rd) Party 206 may perform 224 an action based uponthe actionable item or changes. EM server 204 may refine 226 one or morealgorithms based upon the sensor data and the determined actionableitem.

In the exemplary embodiment, 3^(rd) Party 206 is a subscriber to aservice that monitors for potential actionable items. For example,3^(rd) Party 206 may be a landlord that owns a plurality of rentalbuildings. EM server 204 may determine 222 that one of the landlord'sbuildings is in need of repairs, that one of the trees in his yard has adisease, that one of the walkways near his building has a dangerouscondition, and/or that one of his tenants is failing to perform propermaintenance, e.g., mow the lawn or perform repairs to the premises. Thenotification of the actionable item may inform the landlord of apreviously unknown issue that requires action on his part. 3^(rd) Party206 may also be a homeowner's association and actionable items mayinclude lawn maintenance, building changes, and/or other issuespotentially related to the homeowner's charter.

In other examples, 3^(rd) Party 206 may be a service provider, such as atree trimmer, a roofer, or other construction company. In theseexamples, 3^(rd) Party 206 may transmit one or more advertisements to aperson associated with the actionable item, such as the homeowner. Forexample, EM server 204 may determine 218 that there is damage to thesiding of the house, determine 222 one or more 3^(rd) Parties 206 thatmay repair the issue, and notify those 3^(rd) Parties 206.

In still other examples, 3^(rd) Party 206 may be a municipal serviceprovider, such as a road repair crew or a building inspector. In theexample of road repair crew, the actionable item may be one or morepotholes or other potential hazards. In some embodiments, the hazard maybe a broken water pipe and/or flooding on the road. In the example of abuilding inspector, EM server 204 may determine 218 that a new additionor out building was added to a property and notify the buildinginspector that there may be a permitting issue. In another example, EMserver 204 may compare the timing of traffic lights to determine ifthere is an issue or if the timing of one or more lights may need to beadjusted.

In still further examples, sensors 105 may observe a vehicular accidentand EM server 204 may use sensor data to recreate the accident andprovide the accident information to the police or the appropriateinsurance companies. In this example, vehicle 100 may not be involved inthe vehicular accident.

In yet another example, sensors 105 may observe weather conditions. Forexample during a hail storm, sensors 105 may measure the size of hailthrough images and the rate of hail based upon the sound of the hailhitting vehicle 100 or the ground. EM server 204 may receive sensor dataabout the hail from multiple vehicles 100 in multiple locations todetermine where the hail fell and how serious it was in different areas.Then EM server 204 may determine 222 one or more construction companiesthat would be interested in this information for lead generationpurposes.

In other examples, 3^(rd) Party 206 may be an insurance provider. The EMserver 204 may analyze the vehicle sensor data, and/or other data,received, such as discussed elsewhere herein, such as using patternrecognition or machine learning techniques. The EM server 204 maydetermine preventive or mitigation recommendations. For instance, imagedata acquired via vehicle sensors may reveal shrubbery to close to aninsured home, or trees with large limbs over handing a roof of theinsured home. Virtual recommendations may be generated by the EM server204, such as recommendations to trim vegetation surrounding the insuredhome, and transmitted to a customer's mobile device. If the customerverifies that the recommendations have been taken, then a homeownersinsurance discount may be generated and applied to their insurancepolicy.

Additionally or alternatively, the EM server 204 may determine that (i)the shingles on a roof of an insured home should be replaced; (ii)siding should be repaired or replaced; (iii) windows or storm windowsshould be upgraded; (iv) doors or garage doors should be upgraded; (v)trees are infected by insects and should be treated (such as viaanalysis of images of leaves); (vi) observed structural insulationefficiency; etc. Recommendations may be transmitted to the customer'smobile device for their review via wireless data transmission over oneor more radio links or wireless communication channels. If the customerperforms the suggested upgrade(s) to their home, an insurance discountmay be generated and applied to their policy.

After insurance-related event, such as one that causes damage to aninsured vehicle or an insured home, vehicle sensor data and/or otherdata may be analyzed to estimate an extent of damage to the insuredvehicle or home, respectively. A virtual proposed insurance claim may begenerated using the damage estimate, and transmitted to the customer'smobile device for their review and/or approval. In case of a vehiclecollision, if damage is severe, the insured vehicle may be deemed a“total loss” for insurance purposes and the total loss claim handlingprocess may commence. In the case that a current insurance-relatedevent, such as a home fire or vehicle collision, is anticipated or hashappened, emergency personnel may be requested to arrive at the scene torender aid.

Exemplary Method for Analyzing Vehicle Environment

FIG. 3 illustrates a flow chart of an exemplary computer-implementedprocess 300 for analyzing the environment of a vehicle as shown in FIG.2. Process 300 may be implemented by a computing device, for example EMserver 204 (shown in FIG. 2). In the exemplary embodiment, EM server 204may be in communication with vehicle computer device 110 (shown inFIG. 1) through a wireless communications network, such as a cellularnetwork. In some embodiments, database 202 (shown in FIG. 2) and EMserver 204 are both part of vehicle computer device 110 and included invehicle 100 (shown in FIG. 1).

In the exemplary embodiment, EM server 204 may receive 305 a pluralityof data from at least one sensor 105 (shown in FIG. 1) associated withvehicle 100. In the exemplary embodiment, the plurality of data mayinclude at least one environmental condition. Examples of anenvironmental condition include, but are not limited to, a condition ofa building, a condition of vegetation, a condition of a publicthoroughfare, a weather condition, and a vehicular accident that vehicle100 was not involved in. Other examples of environmental conditions arelisted above. In the exemplary embodiment, vehicle 100 includes aplurality of sensors 105 that provide data to vehicle controller 110.Vehicle controller 110 transmits the sensor data to EM server 204 foranalysis.

In the exemplary embodiment, EM server 204 may analyze 310 the pluralityof data to determine the at least one environmental condition. In someembodiments, EM server 204 may compare the received plurality of data tohistorical sensor data to determine the environmental condition. Inother embodiments, EM server 204 may use algorithms of potential issuesand known examples of environmental conditions to determine if one ofthe known examples is in the received sensor data.

In the exemplary embodiment, EM server 204 may determine 315 at leastone actionable item based upon the determined at least one environmentalcondition. EM server 204 may determine 320 at least one provider or3^(rd) Party 206 (shown in FIG. 3) based upon the actionable item. Insome embodiments, the 3^(rd) Party 206 is a user, who set up a useraccount to receive information about the determined environmentalcondition or actionable items. Examples of 3^(rd) Parties 206 mayinclude municipal agencies, landlords, and advertisers. For example, EMserver 204 may determine 320 a landlord for the actionable item basedupon the location of vehicle 100 at the time that the sensor data wastaken. Using the GPS location information, EM server 204 may determinethe address of the building being imaged and determine the landlord forthat building, who has set-up an account to receive notifications.

In the scenario where the 3^(rd) Party 206 is an insurance provider, theactionable item may be to generate a quote and/or a discount forhomeowners or auto insurance based upon EM server 204 analysis of thevehicle sensor data collected. For instance, features and status of ahome or vehicle may be determined from processor analysis (such asperforming pattern recognition or machine learning techniques on imagedata), and risk, or lack thereof, may be assessed or estimated by theprocessor.

Additionally or alternatively, after an insurance-related event, such asa tornado or wind storm for an insured home or a vehicle collision foran insured vehicle, the amount and/or level of severity of damage to theinsured asset may be estimated from the sensor data received. Forinstance, a vehicle with extensive damage of a high percentage ofpre-collision vehicle value may be deemed a total loss for insurancepurposes.

Referring back to FIG. 3, EM server 204 may then transmit 325 a messageto the determined 3^(rd) Party provider 206. The message may include theactionable item, the environmental condition, sensor data, and/or anyother information required and/or requested by the 3^(rd) Party. In someembodiments, EM server 204 may collect sensor data from a plurality ofvehicles 100 and use that sensor data to determine 315 a plurality ofactionable items. In these embodiments, EM server 204 may transmit abatch message to 3^(rd) Party 206 with actionable items associated with3^(rd) Party's interests.

Exemplary Computer Network

FIG. 4 depicts a simplified block diagram of an exemplary system 400 forimplementing process 200 shown in FIG. 2. In the exemplary embodiment,system 400 may be used for analyzing the environment of a vehicle basedupon sensor data, determining one or more actionable items based uponthe environment, and communicating with providers to perform thoseactionable items. As described below in more detail, environmentmonitoring (“EM”) server 204 may be configured to receive a plurality ofdata from at least one sensor 105 associated with vehicle 100 (bothshown in FIG. 1). The plurality of data includes at least oneenvironmental condition. EM server 204 may also be configured to analyzethe plurality of data to determine the at least one environmentalcondition, determine at least one actionable item based upon the atleast one environmental condition, determine at least one provider 206(shown in FIG. 2) based upon the actionable item, and transmit a messageto the at least one provider 206. The message includes the at least oneactionable item to facilitate communication to providers about potentialactionable items.

In the exemplary embodiment, user computer devices 405 are computersthat include a web browser or a software application, which enables usercomputer devices 405 to access EM server 204 using the Internet or othernetwork. More specifically, user computer devices 405 arecommunicatively coupled to the Internet through many interfacesincluding, but not limited to, at least one of a network, such as theInternet, a local area network (LAN), a wide area network (WAN), or anintegrated services digital network (ISDN), a dial-up-connection, adigital subscriber line (DSL), a cellular phone connection, and a cablemodem. User computer devices 405 may be any device capable of accessingthe Internet including, but not limited to, a desktop computer, a laptopcomputer, a personal digital assistant (PDA), a cellular phone, asmartphone, a tablet, a phablet, wearable electronics, smart watch, orother web-based connectable equipment or mobile devices. In someembodiments, user computer device 405 is associated with thepolicyholder of an account associated with vehicle 100. In otherembodiments, user computer device 405 is associated with a third party,such as 3^(rd) Party Provider 206.

A database server 410 may be communicatively coupled to a database 202that stores data. In one embodiment, database 202 may include 3^(rd)Party providers, sensor data, historical data, environmental conditions,and/or actionable items. In the exemplary embodiment, database 202 maybe stored remotely from EM server 204. In some embodiments, database 202may be decentralized. In the exemplary embodiment, a user may accessdatabase 202 via user computer devices 405 by logging onto EM server204, as described herein.

EM server 204 may be communicatively coupled with the user computerdevices 405. In some embodiments, EM server 204 may be associated with,or is part of a computer network associated with a manufacturer ofvehicle 100, or in communication with the manufacturer's computernetwork (not shown). In other embodiments, EM server 204 may beassociated with a third party. In some embodiments, vehicle controller110 may include EM server 204. In other embodiments, EM server 204 maybe remote from vehicle computer device 110 and may communicate withvehicle computer device 110 via a wireless connection, such as acellular connection. In some embodiments, EM server 204 may beassociated with, or is part of a computer network associated with aninsurance provider, or in communication with the insurance provider'scomputer network (not shown). In other embodiments, EM server 204 may beassociated with a third party and is merely in communication with theinsurance provider's computer network.

One or more vehicle computer devices 110 may be communicatively coupledwith EM server 204 through the Internet or a cellular network. In theexemplary embodiment, vehicle computer devices 110 are computersincluded in vehicles 100 that include a software application, whichenables vehicle computer devices 110 to access EM server 204 using theInternet or other network. More specifically, vehicle computer devices110 are communicatively coupled to the Internet through many interfacesincluding, but not limited to, at least one of a network, such as theInternet, a local area network (LAN), a wide area network (WAN), or anintegrated services digital network (ISDN), a dial-up-connection, adigital subscriber line (DSL), a cellular phone connection, and a cablemodem. In some embodiments, vehicle computer device 110 may be capableof communicating with EM server 204 while in transit. In otherembodiments, vehicle computer device 110 may be capable of communicatingwith EM server 204 while vehicle 100 is at rest, such as at a stoplight.In still other embodiments, vehicle computer device 110 may be capableof communicating with EM server 204 while vehicle 100 is parked, such asat a recharging station (not shown).

Vehicle computer device 110 may also include one or more sensors 105.Vehicle computer device 110 may be configured to receive data fromsensors 105 and transmit sensor data to EM server 204.

In the exemplary embodiment, sensor 105 may be a configured to detectone or more conditions of the environment around vehicle 100. In otherembodiments, sensor 105 may be configured to detect one or moreconditions of one or more occupants of vehicle 100, such as driver 115and/or passengers 120 (both shown in FIG. 1).

Exemplary Client Device

FIG. 5 depicts an exemplary configuration of user computer device 405shown in FIG. 4, in accordance with one embodiment of the presentdisclosure. User computer device 502 may be operated by a user 501. Usercomputer device 502 may include, but is not limited to, user computerdevices 405 (shown in FIG. 4), vehicle controller 110 (shown in FIG. 1),and mobile device 125 (shown in FIG. 1). User computer device 502 mayinclude a processor 505 for executing instructions. In some embodiments,executable instructions are stored in a memory area 510. Processor 505may include one or more processing units (e.g., in a multi-coreconfiguration). Memory area 510 may be any device allowing informationsuch as executable instructions and/or transaction data to be stored andretrieved. Memory area 510 may include one or more computer readablemedia.

User computer device 502 may also include at least one media outputcomponent 515 for presenting information to user 501. Media outputcomponent 515 may be any component capable of conveying information touser 501. In some embodiments, media output component 515 may include anoutput adapter (not shown) such as a video adapter and/or an audioadapter. An output adapter may be operatively coupled to processor 505and operatively coupleable to an output device such as a display device(e.g., a cathode ray tube (CRT), liquid crystal display (LCD), lightemitting diode (LED) display, or “electronic ink” display) or an audiooutput device (e.g., a speaker or headphones).

In some embodiments, media output component 515 may be configured topresent a graphical user interface (e.g., a web browser and/or a clientapplication) to user 501. A graphical user interface may include, forexample, an online store interface for viewing and/or purchasing items,and/or a wallet application for managing payment information. In someembodiments, user computer device 502 may include an input device 520for receiving input from user 501. User 501 may use input device 520 to,without limitation, select and/or enter one or more items to purchaseand/or a purchase request, or to access credential information, and/orpayment information.

Input device 520 may include, for example, a keyboard, a pointingdevice, a mouse, a stylus, a touch sensitive panel (e.g., a touch pad ora touch screen), a gyroscope, an accelerometer, a position detector, abiometric input device, and/or an audio input device. A single componentsuch as a touch screen may function as both an output device of mediaoutput component 515 and input device 520.

User computer device 502 may also include a communication interface 525,communicatively coupled to a remote device such as EM server 204 (shownin FIG. 2). Communication interface 525 may include, for example, awired or wireless network adapter and/or a wireless data transceiver foruse with a mobile telecommunications network.

Stored in memory area 510 are, for example, computer readableinstructions for providing a user interface to user 501 via media outputcomponent 515 and, optionally, receiving and processing input from inputdevice 520. A user interface may include, among other possibilities, aweb browser and/or a client application. Web browsers enable users, suchas user 501, to display and interact with media and other informationtypically embedded on a web page or a website from EM server 204. Aclient application allows user 501 to interact with, for example, EMserver 204. For example, instructions may be stored by a cloud service,and the output of the execution of the instructions sent to the mediaoutput component 515.

Processor 505 executes computer-executable instructions for implementingaspects of the disclosure. In some embodiments, the processor 505 istransformed into a special purpose microprocessor by executingcomputer-executable instructions or by otherwise being programmed. Forexample, the processor 505 may be programmed with the instruction suchas illustrated in FIG. 7.

In some embodiments, user computer device 502 may include, or be incommunication with, one or more sensors, such as sensor 105 (shown inFIG. 1). User computer device 502 may be configured to receive data fromthe one or more sensors and store the received data in memory area 510.Furthermore, user computer device 502 may be configured to transmit thesensor data to a remote computer device, such as EM server 204, throughcommunication interface 525.

Exemplary Server Device

FIG. 6 depicts an exemplary configuration of server 204 shown in FIG. 4,in accordance with one embodiment of the present disclosure. Servercomputer device 601 may include, but is not limited to, database server410 (shown in FIG. 4), EM server 204 (shown in FIG. 2), and vehiclecontroller 110 (shown in FIG. 1). Server computer device 601 may alsoinclude a processor 605 for executing instructions. Instructions may bestored in a memory area 610. Processor 605 may include one or moreprocessing units (e.g., in a multi-core configuration).

Processor 605 may be operatively coupled to a communication interface615 such that server computer device 601 is capable of communicatingwith a remote device such as another server computer device 601, mobiledevice 125 (shown in FIG. 1), vehicle computer device 110 (shown in FIG.1), user computer device 405 (shown in FIG. 4), and EM server 204. Forexample, communication interface 615 may receive requests from usercomputer devices 405 via the Internet, as illustrated in FIG. 4.

Processor 605 may also be operatively coupled to a storage device 634.Storage device 634 may be any computer-operated hardware suitable forstoring and/or retrieving data, such as, but not limited to, dataassociated with database 202 (shown in FIG. 2). In some embodiments,storage device 634 may be integrated in server computer device 601. Forexample, server computer device 601 may include one or more hard diskdrives as storage device 634.

In other embodiments, storage device 634 may be external to servercomputer device 601 and may be accessed by a plurality of servercomputer devices 601. For example, storage device 634 may include astorage area network (SAN), a network attached storage (NAS) system,and/or multiple storage units such as hard disks and/or solid statedisks in a redundant array of inexpensive disks (RAID) configuration.

In some embodiments, processor 605 may be operatively coupled to storagedevice 634 via a storage interface 620. Storage interface 620 may be anycomponent capable of providing processor 605 with access to storagedevice 634. Storage interface 620 may include, for example, an AdvancedTechnology Attachment (ATA) adapter, a Serial ATA (SATA) adapter, aSmall Computer System Interface (SCSI) adapter, a RAID controller, a SANadapter, a network adapter, and/or any component providing processor 605with access to storage device 634.

Processor 605 may execute computer-executable instructions forimplementing aspects of the disclosure. In some embodiments, theprocessor 605 may be transformed into a special purpose microprocessorby executing computer-executable instructions or by otherwise beingprogrammed. For example, the processor 605 may be programmed with theinstruction such as illustrated in FIG. 3.

Exemplary Vehicular Crash Detection

FIG. 7 illustrates a flow chart of an exemplary computer-implementedprocess 700 for detecting a vehicular crash using system 400 shown inFIG. 4. Process 700 may be implemented by a computing device, forexample vehicle computer device 110 (shown in FIG. 4). In someembodiments, process 700 may be implemented by EM server 204 (shown inFIG. 2). In the exemplary embodiment, vehicle computer device 110 may bein communication with EM server 204.

In the exemplary embodiment, vehicle computer device 110 receives 705data from at least one sensor 105 (shown in FIG. 1). In the exemplaryembodiment, at least one sensor 105 may be one or more of plurality ofsensors 105 (shown in FIG. 1) in vehicle 100.

Vehicle computer device 110 determines 710 that a potential vehicularcrash is imminent based upon the received sensor data. For example, inthe exemplary embodiment, sensor 105 is an external sensor and may showthat another vehicle is about to collide with vehicle 100. Or sensor 105may be an impact sensor or any other sensor that allows vehicle computerdevice 110 to work as described herein.

In some embodiments, vehicle computer device 110 generates a scenariomodel of the potential vehicular crash based upon the received sensordata. Scenario models may predict damage to vehicle 100 and injuriesthat may be experiences by driver 115 and passengers 120 (both shown inFIG. 1) of vehicle 100. In the exemplary embodiment, vehicle computerdevice 110 accesses a database, such as database 202 (shown in FIG. 2).Database 202 may contain a plurality of crash scenarios and the sensordata associated with these crash scenarios. The scenarios may be basedupon information from vehicle crash testing facilities, from pastcrashes that EM server 204 has analyzed, and/or from other sources thatallow vehicle computer device 110 to operate as described here. Vehiclecomputer device 110 compares the received sensor data with the differentstored crash scenarios to generate a scenario model that is the mostlikely match for the imminent vehicular crash. In some furtherembodiments, vehicle computer device 110 may communicate the sensor datato EM server 204, where EM server 204 may generate the scenario model.

In some embodiments, vehicle computer device 110 generates a pluralityof scenario models that may fit the sensor data received. Vehiclecomputer device 110 may then rank the generated scenarios based upon thelikelihood or degree of certainty that the scenario is correct. In somefurther embodiments, vehicle computer device 110 may compare the degreeof certainty to a predetermined threshold.

In the exemplary embodiment, vehicle computer device 110 performs 715 atleast one action to reduce the severity of the potential vehicular crashprior to impact. In some embodiments, the action that vehicle computerdevice 110 performs 715 may be to adjust the position or situation ofvehicle 100 at the point of impact. In these embodiments, vehiclecomputer device 110 may determine a position of vehicle 100 to reducedamage to at least one of one or more occupants of the vehicle and thevehicle based upon the scenario model. Vehicle computer device 110 mayinstruct vehicle 100 to adjust its position to the determined positionto lessen the impact. For example, vehicle computer device 110 mayinstruct vehicle 100 to turn one or more wheels to readjust vehicle'sposition. In other examples, vehicle 100 may include hydraulics or someother component that allows vehicle 100 to raise or lower portions ofitself.

In these examples, vehicle computer device 110 may instruct vehicle 100to raise or lower a portion of itself to redirect how forces may impactthe vehicle during impact. In some further examples, vehicle 100 mayhave one or more inflatable external components that vehicle computerdevice 110 may be able to instruct vehicle 100 to inflate prior toimpact to cause forces in the impact to be redirected.

In another embodiment, vehicle computer device 110 may receive data fromsensors 105 about driver 115 and passengers 120 of vehicle 100. In thisembodiment, vehicle computer device 110 may be able to use that sensordata to determine a position and a direction of facing of at least oneoccupant of the vehicle. Then using the scenario model, vehicle computerdevice 110 may be able to determine an advantageous direction of facingfor the at least one occupant. Vehicle computer device 110 may thengenerate a sound through the audio system of vehicle 100, such a horn oralarm sound. The sound would be generated to cause the at least oneoccupant to change to the advantageous direction of facing. For example,vehicle computer device 110 may generate a honking sound to cause thepassenger to turn around to prevent or reduce potential injuries duringthe imminent vehicular crash.

Exemplary Computer Device

FIG. 8 depicts a diagram 800 of components of one or more exemplarycomputing devices 810 that may be used in system 400 shown in FIG. 4. Insome embodiments, computing device 810 may be similar to EM server 204(shown in FIG. 2). Database 820 may be coupled with several separatecomponents within computing device 810, which perform specific tasks. Inthis embodiment, database 820 may include 3^(rd) Party providers 822,sensor data 824, environmental conditions 826, and/or actionable items828. In some embodiments, database 820 is similar to database 202 (shownin FIG. 2).

Computing device 810 may include the database 820, as well as datastorage devices 830. Computing device 810 may also include acommunication component 840 for receiving 305 a plurality of data andtransmitting 325 a message (both shown in FIG. 3), such as via wirelesscommunication or data transmission via radio links or wirelesscommunication channels. Computing device 810 may further include ananalyzing component 850 for analyzing 310 the plurality of data (shownin FIG. 3). Moreover, computing device 810 may include a determiningcomponent 860 for determining 315 at least one actionable item anddetermining 320 at least one provider (both shown in FIG. 3). Aprocessing component 870 may assist with execution ofcomputer-executable instructions associated with the system.

Exemplary Vehicle Environment Analysis

FIG. 9 illustrates a flow chart of another exemplarycomputer-implemented process for analyzing the environment of a vehicleshown in FIG. 2. Process 900 may be implemented by a computing device,for example EM server 204 (shown in FIG. 2). In the exemplaryembodiment, EM server 204 may be in communication with vehicle computerdevice 110 (shown in FIG. 1) through a wireless communications network,such as a cellular network, and/or over one or more radio links orwireless communication channels. In some embodiments, database 202(shown in FIG. 2) and EM server 204 are both part of vehicle computerdevice 110 and included in vehicle 100 (shown in FIG. 1).

In the exemplary embodiment, EM server 204 may receive 905 a pluralityof data from at least one sensor 105 (shown in FIG. 1) associated withvehicle 100. In the exemplary embodiment, the plurality of data mayinclude at least one environmental condition. Examples of anenvironmental condition include, but are not limited to, a condition ofa building, a condition of vegetation, a condition of a publicthoroughfare, a weather condition, and a vehicular accident that vehicle100 was not involved in. Other examples of environmental conditions arelisted above. In the exemplary embodiment, vehicle 100 includes aplurality of sensors 105 that provide data to vehicle controller 110.Vehicle controller 110 transmits the sensor data to EM server 204 foranalysis.

In the exemplary embodiment, EM server 204 may analyze 910 the pluralityof data to determine the at least one environmental condition. In someembodiments, EM server 204 may compare the received plurality of data tohistorical sensor data to determine the environmental condition. Inother embodiments, EM server 204 may use algorithms of potential issuesand known examples of environmental conditions to determine if one ofthe known examples is in the received sensor data.

In the exemplary embodiment, EM server 204 may determine 915 at leastone actionable item based upon the determined at least one environmentalcondition. EM server 204 may determine 920 an insurance policyassociated with the at least one actionable item. For example, EM server204 may determine 920 an associated insurance policy by determining anaddress associated with the at least one actionable item. Using the GPSlocation information, EM server 204 may determine the address of thebuilding being imaged. EM server 204 may then look up the address indatabase 202 to determine 920 if there is an insurance policy associatedwith that address.

EM server 204 may then generate 925 a proposed virtual insurance claimbased upon the at least one actionable item. For example, theenvironmental condition may be damage to the siding of a house and theactionable item be the needed repairs. The house may be insured and EMserver 204 may generate a proposed virtual claim for the damage basedupon the insurance policy and the needed repairs.

In some embodiments, EM server 204 may determine a cost and/or value ofthe virtual claim based upon the actionable item. In some furtherembodiments, EM server 204 may determine one or more recommended 3^(rd)Party providers 206 to rectify the actionable items. In some furtherembodiments, EM server 204 may request bids from 3^(rd) Party Providers206 to determine the costs and/or values of actionable items.

In still further embodiments, EM server 204 may generate 925 a pluralityof potential virtual claims based upon the actionable items. EM server204 may then rank the plurality of potential claims to determine whichones are the most appropriate for the actionable items beforegenerating. EM server 204 may use other methods to determine the mostappropriate virtual claims to generate.

EM server 204 may present the proposed virtual insurance claim to thecustomer for their review and/or approval. For instance, the EM server204 may transmit the proposed virtual insurance claim to the customer'smobile device or vehicle display, such as via wireless communication ordata transmission over one or more radio frequency links or wirelesscommunication channels. After which, the customer may approve theproposed virtual insurance claim, such as by pressing an icon of theirmobile device or vehicle display. The approval may then be transmittedvia wireless communication or data transmission back to the EM server204.

After which, EM server 204 may transmit 930 the virtual insurance claimsto an insurance provider, such as the one associated with the insurancepolicy. The insurance provider may then complete the virtual claimand/or determine other claims for the insurance policy based upon theactionable items and environmental conditions.

Additionally or alternatively, after an insurance-related event, such asa tornado or wind storm for an insured home or a vehicle collision foran insured vehicle, the amount and/or level of severity of damage to theinsured asset may be estimated from the sensor data received. Forinstance, a vehicle with extensive damage of a high percentage ofpre-collision vehicle value may be deemed a total loss for insurancepurposes. Referring back to FIG. 9, EM server 204 may then generate 925and transmit 930 one or more virtual claims to the insurance provider.The virtual claims may include the actionable item, the environmentalcondition, sensor data, and/or any other information required and/orrequested by the insurance provider. In some embodiments, EM server 204may collect sensor data from a plurality of vehicles 100 and use thatsensor data to determine 915 a plurality of actionable items.

Exemplary Method for Analyzing Vehicle Environment

FIG. 10 illustrates a flow chart of a further exemplarycomputer-implemented process for analyzing the environment of a vehicleshown in FIG. 2. Process 1000 may be implemented by a computing device,for example EM server 204 (shown in FIG. 2). In the exemplaryembodiment, EM server 204 may be in communication with vehicle computerdevice 110 (shown in FIG. 1) through a wireless communications network,such as a cellular network. In some embodiments, database 202 (shown inFIG. 2) and EM server 204 are both part of vehicle computer device 110and included in vehicle 100 (shown in FIG. 1).

In the exemplary embodiment, EM server 204 may receive 1005 a pluralityof data from at least one sensor 105 (shown in FIG. 1) associated withvehicle 100. In the exemplary embodiment, the plurality of data mayinclude at least one environmental condition. Examples of anenvironmental condition include, but are not limited to, a condition ofa building, a condition of vegetation, a condition of a publicthoroughfare, a weather condition, and a vehicular accident that vehicle100 was not involved in. Other examples of environmental conditions arelisted above. In the exemplary embodiment, vehicle 100 includes aplurality of sensors 105 that provide data to vehicle controller 110.Vehicle controller 110 transmits the sensor data to EM server 204 foranalysis.

In the exemplary embodiment, EM server 204 may analyze 1010 theplurality of data to determine the at least one environmental condition.In some embodiments, EM server 204 may compare the received plurality ofdata to historical sensor data to determine the environmental condition.In other embodiments, EM server 204 may use algorithms of potentialissues and known examples of environmental conditions to determine ifone of the known examples is in the received sensor data.

In the exemplary embodiment, EM server 204 may determine 1015 acondition of a building based upon the at least one environmentalcondition. For instance, features and status of the building may bedetermined from processor analysis (such as performing patternrecognition or machine learning techniques on image data), and risk, orlack thereof, may be assessed or estimated by the processor or EM server204. Using the GPS location information, EM server 204 may determine theaddress of the building being imaged.

EM server 204 may determine 1020 an insurance product for the buildingbased upon the determine condition of the building. For example, if thebuilding is a home, then EM server 204 may determine 1020 a homeowner'sinsurance policy for the home based upon the condition of the home. EMserver 204 may use the determined address to determine additionalinformation that may be used in determining 1020 an insurance product.

EM server 204 may then generate 1025 an insurance quote for theinsurance product. In the exemplary embodiment, EM server 204 transmitsthe insurance quote and the determined product to a 3^(rd) PartyProvider 206 (shown in FIG. 2), such as an insurance provider. In otherembodiments, EM server 204 may transmit the insurance quote to thehomeowner. The insurance provider may then provide the quote to thehomeowner. The insurance quote and/or determined insurance product mayinclude the environmental condition, sensor data, and/or any otherinformation required and/or requested by 3^(rd) Party 206. In someembodiments, EM server 204 may collect sensor data from a plurality ofvehicles 100 and use that sensor data to determine 315 a plurality ofactionable items.

In some embodiments, EM server 204 may determine at least one actionableitem based upon the determined at least one environmental condition. EMserver 204 may then adjust the insurance quote based upon the at leastone actionable item.

Exemplary Embodiments & Functionality

In one aspect, a computer system for analyzing the environment of avehicle may be provided. The computer system may include at least oneprocessor in communication with at least one memory device. The at leastone processor (local or remote to the vehicle) may be configured orprogrammed to: (1) receive a plurality of data from at least one sensorassociated with a vehicle (such as via wireless communication or datatransmission over one or more radio links or communication channels),where the plurality of data includes at least one environmentalcondition; (2) analyze the plurality of data to determine the at leastone environmental condition; (3) determine at least one actionable itembased upon the at least one environmental condition; (4) determine atleast one provider based upon the actionable item; and/or (5) transmit amessage to the at least one provider (such as via wireless communicationor data transmission over one or more radio links or wirelesscommunication channels), wherein the message includes the at least oneactionable item.

The environmental condition may be proximate to the vehicle at a pointin time. The computer system may achieve the above results where theenvironmental condition is proximate to the vehicle at a plurality ofseparate points in time and the computer system determines the at leastone environmental condition by comparing data associated with theplurality of separate points in time. The environmental condition maybe, but is not limited to, a condition of a building, a condition ofvegetation, a condition of a public thoroughfare, a weather condition,and a vehicular collision that the vehicle was not involved in.

A further enhancement may be where the plurality of data includeslocation data, such as from a GPS unit. And the processor may determinea location associated with the at least one environmental conditionbased upon the plurality data including the location data.

A further enhancement may be where the computer system may transmit amessage to one or more emergency services based upon the scenario model.The one or more emergency services may include, but are not limited to,a towing service, an emergency medical service provider, a firedepartment, a police department, and/or some other emergency responder.The computer system may select the one or more emergency services totransmit to based upon the scenario model and the location of thevehicular crash.

The computer system may achieve the above results by storing a databaseof historical sensor data based upon past sensor data that the vehicleobserved. The computer system may then compare the database ofhistorical sensor data to the received sensor data and determine the atleast one environmental condition based upon the comparison. Thecomputer system may also achieve the above results by storing a databaseof historical data from a plurality of vehicles and using that databaseto determine the at least one environmental condition. A furtherenhancement may be where the computer system may be configured toinclude a database of potential environmental conditions that may becompared to the received sensor data to determine the at least oneenvironmental condition.

The sensor data described herein may include, but is not limited to,pictures and/or images of around the vehicle, 3D scans of theenvironment around the vehicle, infrared images, the velocity of thevehicle, vibrational data, travel timing data, the acceleration of thevehicle, the location of the vehicle, the direction of travel of thevehicle, one or more changes in velocity, one or more changes indirection of the vehicle, a number of occupants in the vehicle, seatbeltsensor data, and seat occupant weight sensor data.

A further enhancement may be where third parties have signed up withuser accounts that are tied to locations. When the computer systemdetects an environmental condition at a location associated with a useraccount, the computer system may transmit a message to the correspondingthird party about the environmental condition. A still furtherenhancement may be where the environmental condition is associated witha potential business opportunity and the third party transmits anadvertisement associated with the environmental condition and/or theactionable item. The actionable item may be a product or service thatthe third party may provide to resolve the actionable item.

Machine Learning & Other Matters

The computer-implemented methods discussed herein may includeadditional, less, or alternate actions, including those discussedelsewhere herein. The methods may be implemented via one or more localor remote processors, transceivers, and/or sensors (such as processors,transceivers, and/or sensors mounted on vehicles or mobile devices, orassociated with smart infrastructure or remote servers), and/or viacomputer-executable instructions stored on non-transitorycomputer-readable media or medium.

Additionally, the computer systems discussed herein may includeadditional, less, or alternate functionality, including that discussedelsewhere herein. The computer systems discussed herein may include orbe implemented via computer-executable instructions stored onnon-transitory computer-readable media or medium.

A processor or a processing element may be trained using supervised orunsupervised machine learning, and the machine learning program mayemploy a neural network, which may be a convolutional neural network, adeep learning neural network, or a combined learning module or programthat learns in two or more fields or areas of interest. Machine learningmay involve identifying and recognizing patterns in existing data inorder to facilitate making predictions for subsequent data. Models maybe created based upon example inputs in order to make valid and reliablepredictions for novel inputs.

Additionally or alternatively, the machine learning programs may betrained by inputting sample data sets or certain data into the programs,such as image, mobile device, vehicle telematics, autonomous vehicle,and/or intelligent home telematics data. The machine learning programsmay utilize deep learning algorithms that may be primarily focused onpattern recognition, and may be trained after processing multipleexamples. The machine learning programs may include Bayesian programlearning (BPL), voice recognition and synthesis, image or objectrecognition, optical character recognition, and/or natural languageprocessing—either individually or in combination. The machine learningprograms may also include natural language processing, semanticanalysis, automatic reasoning, and/or machine learning.

In supervised machine learning, a processing element may be providedwith example inputs and their associated outputs, and may seek todiscover a general rule that maps inputs to outputs, so that whensubsequent novel inputs are provided the processing element may, basedupon the discovered rule, accurately predict the correct output. Inunsupervised machine learning, the processing element may be required tofind its own structure in unlabeled example inputs. In one embodiment,machine learning techniques may be used to extract data about the mobiledevice or vehicle from device details, mobile device sensors,geolocation information, image data, and/or other data.

In one embodiment, a processing element may be trained by providing itwith a large sample of phone and/or online credentials with knowncharacteristics or features. Such information may include, for example,fingerprint, device print, verification codes, PBQA, and/or passivevoice analysis.

Based upon these analyses, the processing element may learn how toidentify characteristics and patterns that may then be applied toanalyzing sensor data, authentication data, image data, mobile devicedata, and/or other data. For example, the processing element may learn,with the user's permission or affirmative consent, to identify the userbased upon the user's device or login information. The processingelement may also learn how to identify different types of environmentalchanges and associated actionable items based upon differences in thereceived sensor data. The processing element may further learn how toidentify an environmental change and/or actionable item based uponpartial or incomplete information and determine a level of certaintythat the environmental change and/or actionable item is correct.

Additional Exemplary Embodiments

In still another aspect, a computer system for detecting a vehicularcrash may be provided. The computer system may include at least oneprocessor, sensor, and/or transceiver in communication with at least onememory device, the at least one processor, sensor, and/or transceiver.The at least one processor may be programmed to (1) receive data fromthe at least one sensor; (2) determine that a potential vehicular crashis imminent based upon the received data; and/or (3) perform at leastone action to reduce a severity of the potential vehicular crash priorto impact. The computer system may include additional, less, oralternate functionality, including that discussed elsewhere herein.

For instance, the data from the at least one sensor may include speed,acceleration, and braking information; and/or image data associated withan area forward of a direction of travel of a vehicle that is acquiredby a video recorder or camera mounted on the vehicle. Determining that apotential vehicular crash is imminent may be based upon applying objectrecognition techniques on the image data acquired by the video recorderor camera mounted on the vehicle. Determining that a potential vehicularcrash is imminent may further be based upon vehicle speed, acceleration,and breaking data. Determining that a potential vehicular crash isimminent may be based upon processor analysis of vehicle speed andacceleration data, and the image data acquired by a vehicle mountedvideo recorder or camera.

The processor may generate a model of the potential vehicular crashbased upon the received data to further analyze. The processor may alsodetermine a position and a direction of facing of at least one occupantof the vehicle and use the model to determine an advantageous directionof facing for the at least one occupant. If one of the occupants is notfacing in an advantageous way, the processor may generate a soundthrough the audio system to cause the at least one occupant to change tothe advantageous direction of facing.

The processor may also use the model to determine a position ororientation of the vehicle to reduce damage to at least one of one ormore occupants of the vehicle and the vehicle itself. The processor maythen instruct the vehicle to adjust position to the determined position.This may be done by instructing the vehicle to turn at least one wheelto adjust position and/or instructing the vehicle to raise or lower atleast a portion of the vehicle. The processor may also instruct thevehicle to inflate a portion of the vehicle to redirect or lessen theimpact.

Determining that a potential vehicular crash is imminent may be basedupon processor analysis of vehicle speed and acceleration data, andanalysis of the image data acquired by a vehicle mounted video recorderor camera that determines whether an object in a direction of travel ofthe vehicle is within a predetermined or threshold distance for thegiven vehicle speed and acceleration.

The sensor data may be analyzed to estimate a severity of the expectedvehicular crash, and the estimated severity of the expected vehicularcrash may be transmitted to a remote server via wireless communicationor data transmission over one or more radio links or wirelesscommunication channels.

The estimated severity of the expected vehicular crash may be determinedbased upon vehicle speed, acceleration, and braking data acquired frommobile device-mounted sensors and/or vehicle-mounted sensors, and a sizeand type of the object determined to be in the direction of travel ofthe vehicle from performing object recognition techniques on the imagedata captured by one or more vehicle-mounted cameras or video recorders.The type of the object determined to be in the direction of travel ofthe vehicle may be a compact vehicle, sport-utility vehicle, truck, orsemi-truck. The type of the object determined to be in the direction oftravel of the vehicle may be a concrete pillar or support, a streetsign, traffic light, or other road marking. The type of the objectdetermined to be in the direction of travel of the vehicle may be ananimal or a tree.

For instance, the sensor data may include vehicle speed, acceleration,and braking information. The sensor data may further include image dataof area in a direction of vehicle travel or otherwise forward of themoving vehicle, the image data being acquired from one or more videorecorders or cameras mounted on the vehicle, a dashboard of the vehicle,or a mobile device traveling within the vehicle.

The method may include analyzing, via the one or more processors, theimage data using object recognition or pattern recognition techniques toidentify objects forward of the moving vehicle. The method may includeusing the results of the object recognition or pattern recognitiontechniques performed on the image data to identify type of objectsforward of the moving vehicle. The object forward of the moving vehicleidentified may be a compact vehicle, sport utility vehicle, or a truck.The object forward of the moving vehicle identified may be a concretepillar or support, a road sign, a traffic light, or mile marker. Theobject forward of the moving vehicle identified may be an animal or atree.

Determining, via the one or more processors, that a vehicle collision isimminent (or likely imminent) based upon analysis of the sensor data mayinclude processor analysis of vehicle speed and acceleration data, anddetermining whether or not an object shown in image data is within apredetermined distance of the vehicle. The one or more processors maydetermine that based upon the sensor data (such as vehicle speed,acceleration, and braking) and distance to an object shown in the imagedata that a collision will occur in 0.5 seconds, 1 second, 2 seconds, 3seconds, etc. For instance, a processor may determine that a vehiclecollision is imminent if it is likely to occur within 1-3 seconds.

Determining, via the one or more processors, an estimated severity ofthe vehicle collision based upon analysis of the sensor data may includeprocessor analysis of vehicle speed and acceleration data, anddetermining a size and type of an object shown in image data forward ofa direction of travel of the vehicle.

Determining, via the one or more processors, an estimated severity ofthe vehicle collision based upon analysis of the sensor data may includeprocessor analysis of vehicle speed and acceleration data, anddetermining a size and type of an object shown in image data forward ofa direction of travel of the vehicle, and a distance to the object.Determining, via the one or more processors, whether the estimatedseverity is above a predetermined threshold may include estimating anamount of vehicle damage from the vehicle collision and estimatingwhether or not the vehicle will be drivable or not.

ADDITIONAL CONSIDERATIONS

As will be appreciated based upon the foregoing specification, theabove-described embodiments of the disclosure may be implemented usingcomputer programming or engineering techniques including computersoftware, firmware, hardware or any combination or subset thereof. Anysuch resulting program, having computer-readable code means, may beembodied or provided within one or more computer-readable media, therebymaking a computer program product, i.e., an article of manufacture,according to the discussed embodiments of the disclosure. Thecomputer-readable media may be, for example, but is not limited to, afixed (hard) drive, diskette, optical disk, magnetic tape, semiconductormemory such as read-only memory (ROM), and/or any transmitting/receivingmedium, such as the Internet or other communication network or link. Thearticle of manufacture containing the computer code may be made and/orused by executing the code directly from one medium, by copying the codefrom one medium to another medium, or by transmitting the code over anetwork.

These computer programs (also known as programs, software, softwareapplications, “apps”, or code) include machine instructions for aprogrammable processor, and can be implemented in a high-levelprocedural and/or object-oriented programming language, and/or inassembly/machine language. As used herein, the terms “machine-readablemedium” “computer-readable medium” refers to any computer programproduct, apparatus and/or device (e.g., magnetic discs, optical disks,memory, Programmable Logic Devices (PLDs)) used to provide machineinstructions and/or data to a programmable processor, including amachine-readable medium that receives machine instructions as amachine-readable signal. The “machine-readable medium” and“computer-readable medium,” however, do not include transitory signals.The term “machine-readable signal” refers to any signal used to providemachine instructions and/or data to a programmable processor.

As used herein, a processor may include any programmable systemincluding systems using micro-controllers, reduced instruction setcircuits (RISC), application specific integrated circuits (ASICs), logiccircuits, and any other circuit or processor capable of executing thefunctions described herein. The above examples are example only, and arethus not intended to limit in any way the definition and/or meaning ofthe term “processor.”

As used herein, the terms “software” and “firmware” are interchangeable,and include any computer program stored in memory for execution by aprocessor, including RAM memory, ROM memory, EPROM memory, EEPROMmemory, and non-volatile RAM (NVRAM) memory. The above memory types areexample only, and are thus not limiting as to the types of memory usablefor storage of a computer program.

In one embodiment, a computer program is provided, and the program isembodied on a computer readable medium. In an exemplary embodiment, thesystem is executed on a single computer system, without requiring aconnection to a sever computer. In a further embodiment, the system isbeing run in a Windows® environment (Windows is a registered trademarkof Microsoft Corporation, Redmond, Wash.). In yet another embodiment,the system is run on a mainframe environment and a UNIX® serverenvironment (UNIX is a registered trademark of X/Open Company Limitedlocated in Reading, Berkshire, United Kingdom). The application isflexible and designed to run in various different environments withoutcompromising any major functionality.

In some embodiments, the system includes multiple components distributedamong a plurality of computing devices. One or more components may be inthe form of computer-executable instructions embodied in acomputer-readable medium. The systems and processes are not limited tothe specific embodiments described herein. In addition, components ofeach system and each process can be practiced independent and separatefrom other components and processes described herein. Each component andprocess can also be used in combination with other assembly packages andprocesses.

As used herein, an element or step recited in the singular and precededby the word “a” or “an” should be understood as not excluding pluralelements or steps, unless such exclusion is explicitly recited.Furthermore, references to “example embodiment” or “one embodiment” ofthe present disclosure are not intended to be interpreted as excludingthe existence of additional embodiments that also incorporate therecited features.

The patent claims at the end of this document are not intended to beconstrued under 35 U.S.C. § 112(f) unless traditionalmeans-plus-function language is expressly recited, such as “means for”or “step for” language being expressly recited in the claim(s).

This written description uses examples to disclose the disclosure,including the best mode, and also to enable any person skilled in theart to practice the disclosure, including making and using any devicesor systems and performing any incorporated methods. The patentable scopeof the disclosure is defined by the claims, and may include otherexamples that occur to those skilled in the art. Such other examples areintended to be within the scope of the claims if they have structuralelements that do not differ from the literal language of the claims, orif they include equivalent structural elements with insubstantialdifferences from the literal language of the claims.

We claim:
 1. A computer system for analyzing the environment of avehicle, the computer system including at least one processor incommunication with at least one memory device, the at least oneprocessor is programmed to: receive a plurality of data from a pluralityof sensors associated with a plurality of vehicles, wherein theplurality of data includes at least one environmental condition at alocation, wherein each sensor of the plurality of sensors receives theplurality of data while the corresponding vehicle travels past thelocation at a plurality of separate points in time; analyze theplurality of data to determine the at least one environmental conditionat the location; determine a condition of a building at the locationbased upon the at least one environmental condition; and generate avirtual insurance claim based upon the condition of the building.
 2. Thecomputer system of claim 1, wherein the processor is further programmedto: determine an insurance product for the building based upon thedetermined condition associated with the building; generate an insurancequote for the insurance product; and transmit the insurance quote to aninsurance provider.
 3. The computer system of claim 2, wherein theprocessor is further programmed to transmit the insurance quote to auser associated with the location.
 4. The computer system of claim 2,wherein the building is a house and the insurance product is homeowner's insurance.
 5. The computer system of claim 2, wherein the atleast one processor is further programmed to: determine at least oneactionable item based upon the at least one environmental conditions;and adjust the insurance quote based upon the at least one actionableitem.
 6. The computer system of claim 1, wherein the condition of abuilding further includes at least one of a condition of vegetation, acondition of a public thoroughfare, and a weather condition.
 7. Thecomputer system of claim 1, wherein the processor is further programmedto determine a plurality of potential claims associated with each of theat least one actionable items.
 8. The computer system of claim 7,wherein the at least one processor is further programmed to: rank theplurality of potential claims based upon one or more predeterminedrules; determine one or more of the potential claims to generate basedupon the ranking; and generate one or more virtual claims based upon thedetermined one or more potential claims.
 9. The computer system of claim1, wherein the processor is further configured to: store a plurality ofhistorical sensor data; and compare to the historical data to determinethe at least one environmental condition.
 10. A computer-implementedmethod for analyzing the environment of a vehicle, the methodimplemented on an environment monitoring (“EM”) server including atleast one processor in communication with at least one memory device,the method comprising: receiving, at the EM server, a plurality of datafrom a plurality of sensors associated with a plurality of vehicles,wherein the plurality of data includes at least one environmentalcondition at a location, wherein each sensor of the plurality of sensorsreceives the plurality of data while the corresponding vehicle travelspast the location at a plurality of separate points in time; analyzing,by the EM server, the plurality of data to determine the at least oneenvironmental condition at the location; determining, by the EM server,a condition of a building at the location based upon the at least oneenvironmental condition; and generating, by the EM server, a virtualinsurance claim based upon the condition of the building.
 11. Thecomputer-implemented method of claim 10 further comprising: determiningan insurance product for the building based upon the determinedcondition associated with the building; generating an insurance quotefor the insurance product; and transmitting the insurance quote to aninsurance provider.
 12. The computer-implemented method of claim 11further comprising transmitting the insurance quote to a user associatedwith the location.
 13. The computer-implemented method of claim 11,wherein the building is a house and the insurance product is homeowner's insurance.
 14. The computer-implemented method of claim 11further comprising: determining at least one actionable item based uponthe at least one environmental conditions; and adjusting the insurancequote based upon the at least one actionable item.
 15. Thecomputer-implemented method of claim 10 further comprising determining aplurality of potential claims associated with each of the at least oneactionable items.
 16. The computer-implemented method of claim 15further comprising: ranking the plurality of potential claims based uponone or more predetermined rules; determining one or more of thepotential claims to generate based upon the ranking; and generating oneor more virtual claims based upon the determined one or more potentialclaims.
 17. The computer-implemented method of claim 10, wherein theenvironmental condition includes at least one of a condition of abuilding, a condition of vegetation, a condition of a publicthoroughfare, and a weather condition.
 18. The computer-implementedmethod of claim 10 further comprising: storing a plurality of historicalsensor data; and comparing to the historical data to determine the atleast one environmental condition.
 19. At least one non-transitorycomputer-readable storage media having computer-executable instructionsembodied thereon, wherein when executed by at least one processor, thecomputer-executable instructions cause the processor to: receive aplurality of data from a plurality of sensors associated with aplurality of vehicles, wherein the plurality of data includes at leastone environmental condition at a location, wherein each sensor of theplurality of sensors receives the plurality of data while thecorresponding vehicle travels past the location at a plurality ofseparate points in time; analyze the plurality of data to determine theat least one environmental condition at the location; determine acondition of a building at the location based upon the at least oneenvironmental condition; and generate a virtual insurance claim basedupon the condition of the building.
 20. The computer-readable storagemedia of claim 19, wherein the computer-executable instructions furthercause the processor to: determine an insurance product for the buildingbased upon the determined condition associated with the building;generate an insurance quote for the insurance product; and transmit theinsurance quote to an insurance provider.